1. Collaborative Research Groups and the DRN OC
Keith Marsolo
PCORnet DRN OC
“Title Slide” format

2. Introduction
The purpose of this webinar is to define PCORnet, specifically in terms of the Distributed Research Network
In order to complete a picture of what types of questions are currently answerable, we will discuss:
The data in the PCORnet Common Data Model (availability and completeness)
Tools that exist to query the data
Discuss:
Plans and processes for additions to the CDM as part of version 3.2
Interaction of CRGs with the Front Door (FD) for query requests

3. PCORnet at a glance (as of February 2017)
More than 110 million patients with an ambulatory visit, inpatient admission, or ED visit in the past 5 years
More than 55 million patients with an ambulatory visit, inpatient admission, or ED visit in the past year
Data standardized to the PCORnet Common Data Model at ~80 DataMarts
Data are routinely updated on a quarterly basis
Recency and completeness of data varies by DataMart
Data generally available from 2010 onward (varies by DataMart and domain)

4. PCORnet is… A Distributed Research Network
Network partners maintain possession of their own data
Network partners provide aggregate results, not patient-level data, to the Coordinating Center for non-study queries
Predominantly EHR data
Standardized across diverse health systems
Biased toward patients who seek care
Highly heterogeneous
Well-suited for counts & summary statistics

5. PCORnet may… (for a subset of DataMarts)
Capture claims/insurance data (~10 DataMarts)
Reflect integrated EHR and claims data
A small number of partners have partially integrated EHR and claims data

6. PCORnet is not well-suited for…
Population-based estimates of incidence and prevalence
Selected sample of patients who seek at least some of their care from participating sites.
Complete longitudinal data capture
This is highly variable across partners and not well- described
Researchers should be prepared to account for loss to follow-up and varying completion rates
Identifying the absence of disease, exposures, or events

7. PCORnet Common Data Model (CDM)

8. PCORnet CDM
A Common Data Model (CDM) is a way of organizing data into a standard structure.
The CDM makes it easier for PCORnet networks to share information with each other by setting common definitions and organizing data so that:
PCORnet can analyze data more quickly.
Different database (RDBMS) platforms can be used by networks to organize their data (data also standardized in SAS to facilitate data analysis).
Networks can analyze their data more easily and efficiently.
Network currently operates on version 3.0
Version 3.1 was released in November and will be characterized in August
The approach PCORnet is using for its CDM mirrors the approaches used by other large national research consortia.

9. PCORnet Common Data Model v3.0
15 PCORnet tables

10. Key Points About Each Table

11. Across all Tables
Percent of DataMarts that populated the table does not mean that all of the fields in the table are populated (Appendix slides report missingness rates)
There is significant diversity in how well-populated each field is within a table
Keep in mind that all IDs (provider ID, patient ID, facility ID, etc.) are pseudoidentifiers
National Provider Identifiers (NPIs) are not captured
Statistics reflect data as of February 2017

12. Demographics Table All DataMarts have populated this table
Hispanic and Race are highly missing, but are likely better populated after 2011 because of Meaningful Use standards*
* Requirements were finalized Sept 2010, but different providers/professionals complied with MU Stage 1 at different times
Key Fields
Birth Date
Sex
Race
Hispanic

13. Enrollment Table All DataMarts have populated this table
Most DataMarts define enrollment by minimum and maximum encounter date for each patient; therefore this may not useful in the typical sense of an “enrollment period”
Key Fields
Start & End Date
Basis (insurance, geography, algorithmic, encounter-based)

14. Encounter Table All DataMarts have populated this table
Encounter types of primary interest are Ambulatory, ED and Inpatient
90% of DataMarts have all 3 of these encounter types
Provider & Facility IDs (these are pseudoidentifiers; not NPIs)
DRG is highly missing
Key Fields
Admit & Discharge Date
Discharge Disposition (discharged alive or expired)
Encounter type
Discharge Status (e.g. nursing home, expired, hospice)
Provider & Facility ID
Diagnosis Related Group (DRG)

15. Diagnosis Table All DataMarts have populated this table
Diagnosis coded as
ICD-9
ICD-10
SNOMED (infrequently used)
Principal flag
Only relevant for inpatient encounters
Well-populated by approximately 75% of DataMarts
Key Fields
Encounter type
Principal diagnosis flag
Diagnosis code

16. Procedures Table All DataMarts have populated this table
Procedures coded as:
NDC/LOINC/Revenue are allowable but generally not included
May include:
orders for lab tests
Injectable/infused outpatient medications are sometimes captured in this table
Key Fields
Encounter type
Procedure code
Procedure source (billing, order, claim)
ICD-9
CPT/HCPCS
LOINC
ICD-10
NDC
Revenue

17. Vitals Table Approximately 95% of DataMarts have populated this table
Smoking & Tobacco – likely better populated after 2011 due to Meaningful Use standards*
* Requirements were finalized Sept 2010, but different providers/professionals complied with MU Stage 1 at different times
Key Fields
Height
BMI
Weight
Smoking
Diastolic & systolic blood pressure
Tobacco

18. Medications – Prescribing Table
Approximately 90% of DataMarts have populated this table
Prescription orders are coded as RxCUIs and DataMarts maps their source data to these codes
Multiple RxCUIs may exist for a given medication order. Preferred hierarchy is provided in the Implementation Guidance
Dose information is not explicitly collected but is captured as part of the preferred RxCUI
Uncertainty of the reliability of mapping at this level
Prescription end date, frequency, and days supply are highly missing
Includes orders for outpatient medication dispensing. May include orders for inpatient medication administration.
Off-the-shelf tool to query this table is anticipated May-August 2017
Key Fields
RxCUI
Quantity
Order date
Refills
Prescription start & end date
Days supply
Frequency

19. Medications – Dispensing Table
Approximately 50% of DataMarts have populated this table
Only captures outpatient medications*
Likely incomplete data capture (DataMarts may only receive certain dispensing feeds)
Dose information is not explicitly collected but is captured as part of the NDC
Off-the-shelf tool to query this table is anticipated May-August 2017
Key Fields
NDC
Days supply
Dispense date
Amount
*The PCORnet CDM does not currently capture inpatient medication administration

20. Lab_Result Table
Approximate 90% of DataMarts have populated this table
The following labs were prioritized for population, although others may be included:
Labs are coded as LOINC codes and DataMarts maps their source data to these codes
A study interested in lab values should plan to do a study-specific data characterization first to better understand the data for the specific lab
Key Fields
LOINC
Specimen Date
Result
Result date
Reference range
A1C
Creatinine
Troponin (Trop T quan, Trop T qual, Trop I)
INR
HGB
LDL
Creatine kinase (CK, CK_MB, CK_MBI)

21. Condition Table
Approximately 70% of DataMarts have populated this table
There is no standardization for the condition variable
No off-the-shelf tool to query this table
Key Fields
Condition
Onset & resolve date
Report date
Status (e.g. active)
Source (e.g. patient-reported)

22. PRO_CM Table Approximately 10% of DataMarts have populated this table
Primarily PROMIS items (small subset)
No off-the-shelf tool to query this table

23. Death Table Approximately 80% of DataMarts have populated this table
Source: deaths reported in EHR and additional sources that DataMarts have access to (e.g. NDI, state death files)
No off-the-shelf tool to query this table
Key Fields
Death date
Source

24. Death Cause Table
Approximately 30% of DataMarts have populated this table
Cause of death coded as:
ICD-9
ICD-10
No off-the-shelf tool to query this table
Key Fields
Cause of death
Source

25. Additional Tables Harvest
Contains information about the specific PCORnet DataMart implementation
PCORnet Trial
Populated for patients in clinical trials

26. Querying the Data in the PCORnet CDM

27. Overview of Query Process
Code is developed centrally by the Coordinating Center (CC)
Query package and results are sent through a secure user portal (PopMedNet)
Querying steps:
CC sends query to participating DataMarts
DataMarts run the query
DataMarts upload aggregate results to PopMedNet
CC compiles results from DataMarts and sends to requestor
Currently only CDRNs are queried via PCORnet query tool

28. PCORnet Query Types: Menu-Driven Queries
Simple interface for query creation incorporated into the PCORnet Query Tool
Query securely distributed to sites for execution against the local database (RDBMS) in PCORnet CDM format
Query generates aggregate data for local review and secure return
Asynchronous by design

30. PCORnet Query Types: SAS Queries
SAS code package designed to execute against SAS datasets in PCORnet CDM format
Distributed via the PCORnet Query Tool
Downloaded and executed locally
Response uploaded and returned via Query Tool

32. Issues to Consider for Distributed Querying
Complexities to consider when developing a stable, distributed querying infrastructure
Common Data Model conformance
Local system implementation variability
Source data size
Programming efficiency
Transparency
Local system implementation variability
Software and hardware
Computing environments
IT environments and configuration
Local expertise

33. Next Steps – CDM v3.2
The DRN OC will develop the next version of the CDM. This expansion will include:
additional elements to existing tables (e.g., more demographics, vitals, lab results)
1-2 new tables (may be optional); potentially an observation table
This expansion needs to be informed by the CRGs
All CRGs submit a request to DRN OC for elements/tables they need by May 31, 2017 with:
A request form template for addition of data elements
Detailed description of new tables/domains – data elements, potential source, any terminology/vocabulary standards, availability across partners, etc.

34. Next Steps – CDM v3.2
Form available on iMeet:

35. Next Steps – CDM v3.2 Provide as much detail as possible:
Will help with assessment
Will assist with future studies that seek to use these elements
DRN OC will review all requests and identify overlap and opportunities for harmonization
Draft CDM specification will be released & follow existing CDM processes
Final draft specification will be submitted to the PCORnet Executive Committee for review and approval

36. Beyond CDM v3.2
Will not be able to incorporate everything into CDM v3.2 as a required element
Observation table would provide a place for CRGs / studies to store elements of interest
Studies could provide funding for partners to obtain these additional elements
Other alternative will be to collect data as part of prospective clinical trials & merge with CDM

37. Nest Steps – CRG FD requests
Multi-phased approach
Phase I:
Table 1 queries for each CRG using PROCEDURES and DIAGNOSES
Phase II:
After CDM expansion and additional tool development, we can reassess additional Table 1 queries

38. “Picture with Caption” format

39. Missingness Rates
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40. Missingness Rates
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